Python 3
import numpy as npimport pandas as pd import plotly.express as pximport osfor dirname, _, filenames in os.walk('/kaggle/input'): for filename in filenames: print(os.path.join(dirname, filename))# Mohammad Shoaib and Amanullah Sarwaridf = pd.read_csv('/Users/Shoaib Bigzad/Desktop/data scince/covid 19 dataset/region_data.csv')df| Unnamed: 0 | Location | day | date | total_number_positive_people | deaths | deaths_increase | total_recoveries | total_recoveries_increase | currently_positive | dismissed_patients | swabs | swabs_increase | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 10 | Toscana | 0 | 24/2/2020 | 0 | 0 | 0.000000 | 0 | 0.000000 | 0 | 0 | 140 | 0.000000 |
| 1 | 24 | Toscana | 1 | 25/2/2020 | 2 | 0 | 0.000000 | 2 | 0.000000 | 2 | 0 | 296 | 111.428570 |
| 2 | 38 | Toscana | 2 | 26/2/2020 | 2 | 0 | 0.000000 | 2 | 0.000000 | 2 | 0 | 363 | 22.635136 |
| 3 | 52 | Toscana | 3 | 27/2/2020 | 2 | 0 | 0.000000 | 2 | 0.000000 | 2 | 0 | 410 | 12.947659 |
| 4 | 66 | Toscana | 4 | 28/2/2020 | 8 | 0 | 0.000000 | 5 | 150.000000 | 7 | 1 | 437 | 6.585366 |
| 5 | 80 | Toscana | 5 | 29/2/2020 | 11 | 0 | 0.000000 | 7 | 40.000000 | 10 | 1 | 531 | 21.510298 |
| 6 | 94 | Toscana | 6 | 01/3/2020 | 13 | 0 | 0.000000 | 7 | 0.000000 | 12 | 1 | 572 | 7.721281 |
| 7 | 108 | Toscana | 7 | 02/3/2020 | 13 | 0 | 0.000000 | 7 | 0.000000 | 12 | 1 | 613 | 7.167832 |
| 8 | 122 | Toscana | 8 | 03/3/2020 | 19 | 0 | 0.000000 | 10 | 42.857143 | 18 | 1 | 697 | 13.703099 |
| 9 | 136 | Toscana | 9 | 04/3/2020 | 38 | 0 | 0.000000 | 17 | 70.000000 | 37 | 1 | 776 | 11.334290 |
| 10 | 150 | Toscana | 10 | 05/3/2020 | 61 | 0 | 0.000000 | 29 | 70.588234 | 60 | 1 | 776 | 0.000000 |
| 11 | 164 | Toscana | 11 | 06/3/2020 | 79 | 0 | 0.000000 | 40 | 37.931034 | 78 | 1 | 1097 | 41.365978 |
| 12 | 178 | Toscana | 12 | 07/3/2020 | 113 | 0 | 0.000000 | 61 | 52.500000 | 112 | 1 | 1331 | 21.330902 |
| 13 | 192 | Toscana | 13 | 08/3/2020 | 166 | 0 | 0.000000 | 98 | 60.655739 | 165 | 1 | 1618 | 21.562735 |
| 14 | 206 | Toscana | 14 | 09/3/2020 | 208 | 1 | 0.000000 | 116 | 18.367348 | 206 | 1 | 2018 | 24.721878 |
| 15 | 220 | Toscana | 15 | 10/3/2020 | 264 | 1 | 0.000000 | 131 | 12.931034 | 260 | 3 | 2573 | 27.502478 |
| 16 | 234 | Toscana | 16 | 11/3/2020 | 320 | 1 | 0.000000 | 141 | 7.633588 | 314 | 5 | 2804 | 8.977847 |
| 17 | 248 | Toscana | 17 | 12/3/2020 | 364 | 5 | 400.000000 | 159 | 12.765958 | 352 | 7 | 3165 | 12.874465 |
| 18 | 262 | Toscana | 18 | 13/3/2020 | 470 | 5 | 0.000000 | 211 | 32.704403 | 455 | 10 | 4049 | 27.930490 |
| 19 | 276 | Toscana | 19 | 14/3/2020 | 630 | 6 | 20.000000 | 247 | 17.061611 | 614 | 10 | 4595 | 13.484811 |
| 20 | 290 | Toscana | 20 | 15/3/2020 | 781 | 8 | 33.333332 | 282 | 14.170040 | 763 | 10 | 5132 | 11.686616 |
| 21 | 304 | Toscana | 21 | 16/3/2020 | 866 | 14 | 75.000000 | 282 | 0.000000 | 841 | 11 | 5910 | 15.159781 |
| 22 | 318 | Toscana | 22 | 17/3/2020 | 1053 | 17 | 21.428572 | 472 | 67.375885 | 1024 | 12 | 6727 | 13.824027 |
| 23 | 332 | Toscana | 23 | 18/3/2020 | 1330 | 22 | 29.411764 | 587 | 24.364407 | 1291 | 17 | 7606 | 13.066746 |
| 24 | 346 | Toscana | 24 | 19/3/2020 | 1482 | 38 | 72.727272 | 679 | 15.672914 | 1422 | 22 | 8873 | 16.657902 |
| 25 | 360 | Toscana | 25 | 20/3/2020 | 1793 | 47 | 23.684210 | 790 | 16.347570 | 1713 | 33 | 10405 | 17.265863 |
| 26 | 374 | Toscana | 26 | 21/3/2020 | 2012 | 72 | 53.191490 | 866 | 9.620254 | 1905 | 35 | 11909 | 14.454589 |
| 27 | 388 | Toscana | 27 | 22/3/2020 | 2277 | 91 | 26.388889 | 921 | 6.351039 | 2144 | 42 | 13264 | 11.377950 |
| 28 | 402 | Toscana | 28 | 23/3/2020 | 2461 | 109 | 19.780220 | 1076 | 16.829533 | 2301 | 51 | 13851 | 4.425513 |
| 29 | 416 | Toscana | 29 | 24/3/2020 | 2699 | 129 | 18.348623 | 1162 | 7.992565 | 2519 | 51 | 15701 | 13.356437 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 813 | 11392 | Toscana | 813 | 17/5/2022 | 1133738 | 10013 | 0.059958 | 435 | -2.466368 | 37488 | 1086237 | 6774006 | 0.035826 |
| 814 | 11406 | Toscana | 814 | 18/5/2022 | 1135444 | 10020 | 0.069909 | 404 | -7.126437 | 36171 | 1089253 | 6776117 | 0.031163 |
| 815 | 11420 | Toscana | 815 | 19/5/2022 | 1137293 | 10027 | 0.069860 | 401 | -0.742574 | 35538 | 1091728 | 6778566 | 0.036142 |
| 816 | 11434 | Toscana | 816 | 20/5/2022 | 1138815 | 10035 | 0.079785 | 386 | -3.740648 | 34427 | 1094353 | 6780404 | 0.027115 |
| 817 | 11448 | Toscana | 817 | 21/5/2022 | 1140291 | 10038 | 0.029895 | 381 | -1.295337 | 34044 | 1096209 | 6782359 | 0.028833 |
| 818 | 11462 | Toscana | 818 | 22/5/2022 | 1141325 | 10040 | 0.019924 | 350 | -8.136483 | 33000 | 1098285 | 6784216 | 0.027380 |
| 819 | 11476 | Toscana | 819 | 23/5/2022 | 1141775 | 10053 | 0.129482 | 366 | 4.571429 | 31848 | 1099874 | 6785057 | 0.012396 |
| 820 | 11490 | Toscana | 820 | 24/5/2022 | 1143749 | 10059 | 0.059684 | 348 | -4.918033 | 31486 | 1102204 | 6786954 | 0.027958 |
| 821 | 11504 | Toscana | 821 | 25/5/2022 | 1145015 | 10063 | 0.039765 | 343 | -1.436782 | 31313 | 1103639 | 6788855 | 0.028010 |
| 822 | 11518 | Toscana | 822 | 26/5/2022 | 1146405 | 10072 | 0.089437 | 328 | -4.373178 | 30149 | 1106184 | 6790720 | 0.027471 |
| 823 | 11532 | Toscana | 823 | 27/5/2022 | 1147463 | 10073 | 0.009929 | 342 | 4.268293 | 29736 | 1107654 | 6791965 | 0.018334 |
| 824 | 11546 | Toscana | 824 | 28/5/2022 | 1148566 | 10076 | 0.029783 | 319 | -6.725146 | 29234 | 1109256 | 6793426 | 0.021511 |
| 825 | 11560 | Toscana | 825 | 29/5/2022 | 1149359 | 10076 | 0.000000 | 322 | 0.940439 | 29167 | 1110116 | 6795068 | 0.024170 |
| 826 | 11574 | Toscana | 826 | 30/5/2022 | 1149679 | 10084 | 0.079397 | 323 | 0.310559 | 27666 | 1111929 | 6795715 | 0.009522 |
| 827 | 11588 | Toscana | 827 | 31/5/2022 | 1151109 | 10092 | 0.079334 | 304 | -5.882353 | 27415 | 1113602 | 6797239 | 0.022426 |
| 828 | 11602 | Toscana | 828 | 01/6/2022 | 1152078 | 10096 | 0.039635 | 271 | -10.855263 | 26837 | 1115145 | 6798545 | 0.019214 |
| 829 | 11616 | Toscana | 829 | 02/6/2022 | 1153139 | 10096 | 0.000000 | 247 | -8.856089 | 26715 | 1116328 | 6799929 | 0.020357 |
| 830 | 11630 | Toscana | 830 | 03/6/2022 | 1153446 | 10099 | 0.029715 | 247 | 0.000000 | 26093 | 1117254 | 6800664 | 0.010809 |
| 831 | 11644 | Toscana | 831 | 04/6/2022 | 1154838 | 10100 | 0.009902 | 230 | -6.882591 | 25625 | 1119113 | 6801914 | 0.018381 |
| 832 | 11658 | Toscana | 832 | 05/6/2022 | 1155620 | 10101 | 0.009901 | 232 | 0.869565 | 25277 | 1120242 | 6803340 | 0.020965 |
| 833 | 11672 | Toscana | 833 | 06/6/2022 | 1155937 | 10113 | 0.118800 | 242 | 4.310345 | 24145 | 1121679 | 6803762 | 0.006203 |
| 834 | 11686 | Toscana | 834 | 07/6/2022 | 1157565 | 10114 | 0.009888 | 239 | -1.239669 | 23665 | 1123786 | 6805261 | 0.022032 |
| 835 | 11700 | Toscana | 835 | 08/6/2022 | 1158838 | 10116 | 0.019775 | 230 | -3.765690 | 23742 | 1124980 | 6806757 | 0.021983 |
| 836 | 11714 | Toscana | 836 | 09/6/2022 | 1160232 | 10118 | 0.019771 | 223 | -3.043478 | 23838 | 1126276 | 6808347 | 0.023359 |
| 837 | 11728 | Toscana | 837 | 10/6/2022 | 1161335 | 10125 | 0.069184 | 215 | -3.587444 | 24143 | 1127067 | 6809600 | 0.018404 |
| 838 | 11742 | Toscana | 838 | 11/6/2022 | 1162512 | 10126 | 0.009877 | 200 | -6.976744 | 24658 | 1127728 | 6810723 | 0.016491 |
| 839 | 11756 | Toscana | 839 | 12/6/2022 | 1163547 | 10126 | 0.000000 | 197 | -1.500000 | 24684 | 1128737 | 6812155 | 0.021026 |
| 840 | 11770 | Toscana | 840 | 13/6/2022 | 1163981 | 10128 | 0.019751 | 219 | 11.167513 | 24395 | 1129458 | 6812587 | 0.006342 |
| 841 | 11784 | Toscana | 841 | 14/6/2022 | 1166162 | 10130 | 0.019747 | 229 | 4.566210 | 24947 | 1131085 | 6814174 | 0.023295 |
| 842 | 11798 | Toscana | 842 | 15/6/2022 | 1167901 | 10134 | 0.039487 | 228 | -0.436681 | 26052 | 1131715 | 6815858 | 0.024713 |
843 rows × 13 columns
​df.head()| Unnamed: 0 | Location | day | date | total_number_positive_people | deaths | deaths_increase | total_recoveries | total_recoveries_increase | currently_positive | dismissed_patients | swabs | swabs_increase | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 10 | Toscana | 0 | 24/2/2020 | 0 | 0 | 0.0 | 0 | 0.0 | 0 | 0 | 140 | 0.000000 |
| 1 | 24 | Toscana | 1 | 25/2/2020 | 2 | 0 | 0.0 | 2 | 0.0 | 2 | 0 | 296 | 111.428570 |
| 2 | 38 | Toscana | 2 | 26/2/2020 | 2 | 0 | 0.0 | 2 | 0.0 | 2 | 0 | 363 | 22.635136 |
| 3 | 52 | Toscana | 3 | 27/2/2020 | 2 | 0 | 0.0 | 2 | 0.0 | 2 | 0 | 410 | 12.947659 |
| 4 | 66 | Toscana | 4 | 28/2/2020 | 8 | 0 | 0.0 | 5 | 150.0 | 7 | 1 | 437 | 6.585366 |
fig = px.line(df, x="date", y="deaths", color='Location', title="Number of deaths")fig.show()fig = px.line(df, x="date", y="total_number_positive_people", color='Location', title="Total number of positive people")fig.show()fig = px.line(df, x="date", y="currently_positive", color='Location', title="Currently positives cases")fig.show()fig = px.line(df, x="date", y="currently_positive", color='Location', title="Currently positives cases")fig.show()df = pd.read_csv('/kaggle/input/covid19-italy-tuscany-data/provinces_data.csv')df| Unnamed: 0 | Location | day | date | total_number_positive_people | deaths | deaths_increase | |
|---|---|---|---|---|---|---|---|
| 0 | 0 | AR | 0 | 24/2/2020 | 0 | 0 | 0.000000 |
| 1 | 1 | FI | 0 | 24/2/2020 | 0 | 0 | 0.000000 |
| 2 | 2 | GR | 0 | 24/2/2020 | 0 | 0 | 0.000000 |
| 3 | 3 | LI | 0 | 24/2/2020 | 0 | 0 | 0.000000 |
| 4 | 4 | LU | 0 | 24/2/2020 | 0 | 0 | 0.000000 |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 10954 | 11796 | PT | 842 | 15/6/2022 | 93378 | 910 | 0.000000 |
| 10955 | 11797 | SI | 842 | 15/6/2022 | 82487 | 537 | 0.186567 |
| 10956 | 11799 | aslCENTRO | 842 | 15/6/2022 | 497422 | 4936 | 0.000000 |
| 10957 | 11800 | aslNO | 842 | 15/6/2022 | 418719 | 3474 | 0.057604 |
| 10958 | 11801 | aslSE | 842 | 15/6/2022 | 251205 | 1585 | 0.126342 |
10959 rows × 7 columns
fig = px.line(df, x="date", y="total_number_positive_people", color='Location', title="Total number of positive people")fig.show()